Genomic prediction in hybrid breeding: I. Optimizing the training set design

Genomic prediction holds great promise for hybrid breeding but optimum composition of the training set (TS) as determined by the number of parents (n(TS)) and crosses per parent (c) has received little attention. Our objective was to examine prediction accuracy (r(a)) of GCA for lines used as parents of the TS (I1 lines) or not (I0 lines), and H0, H1 and H2 hybrids, comprising crosses of type I0 x I0, I1 x I0 and I1 x I1, respectively, as function of n(TS) and c. In the theory, we developed estimates for r(a) of GBLUPs for hybrids: (i)(r) over cap (a) based on the expected prediction accuracy, and (ii) (r) over tilde (a) based on r(a) of GBLUPs of GCA and SCA effects. In the simulation part, hybrid populations were generated using molecular data from two experimental maize data sets. Additive and dominance effects of QTL borrowed from literature were used to simulate six scenarios of traits differing in the proportion (tau(SCA)= 1%, 6%, 22%) of SCA variance in sigma(2)(G) and heritability (h(2) = 0.4, 0.8). Values of (r) over tilde (a) and (r) over cap (a) closely agreed with r(a) for hybrids. For given size N-TS = n(TS)xc of TS, r(a) of H0 hybrids and GCA of I0 lines was highest for c = 1. Conversely, for GCA of I1 lines and H1 and H2 hybrids, c = 1 yielded lowest r(a) with concordant results across all scenarios for both data sets. In view of these opposite trends, the optimum choice of c for maximizing selection response across all types of hybrids depends on the size and resources of the breeding program.

Automated summary

Genomic prediction in hybrid breeding depends on the composition of the training set. This study investigates the prediction accuracy of GCA for different types of parents and hybrids, determined by the number of parents and crosses per parent. The results show that for GCA of I0 parents and H0 hybrids, c = 1 yields the highest accuracy, while for GCA of I1 parents and H1, H2 hybrids, c = 1 yields the lowest accuracy.